Enhancement and verification of a machined surface quality for glass milling operation using CBN grinding tool-Taguchi approach

Nowadays, the demand for high product quality focuses extensive attention to the quality of machined surface. The (CNC) milling machine facilities provides a wide variety of parameters set-up, making the machining process on the glass excellent in manufacturing complicated special products compared...

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Bibliographic Details
Main Authors: Sayuti, Mohd, Sarhan, Ahmed Aly Diaa Mohammed, Fadzil, M., Abd Shukor, Mohd Hamdi
Format: Article
Published: Springer Verlag 2012
Subjects:
Online Access:http://eprints.um.edu.my/7254/
https://doi.org/10.1007/s00170-011-3657-z
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Summary:Nowadays, the demand for high product quality focuses extensive attention to the quality of machined surface. The (CNC) milling machine facilities provides a wide variety of parameters set-up, making the machining process on the glass excellent in manufacturing complicated special products compared with other machining processes. However, the application of grinding process on the CNC milling machine could be an ideal solution to improve the product quality, but adopting the right machining parameters is required. Taguchi optimization method was used to estimate optimum machining parameters with standard orthogonal array L16 (44) to replace the conventional trial and error method as it is time-consuming. Moreover, analyses on surface roughness and cutting force are applied which are partial determinant of the quality of surface and cutting process. These analyses are conducted using signal to noise (S/N) response analysis and the analysis of variance (Pareto ANOVA) to determine which process parameters are statistically significant. In glass milling operation, several machining parameters are considered to be significant in affecting surface roughness and cutting forces. These parameters include the lubrication pressure, spindle speed, feed rate, and depth of cut as control factors. While, the lubrication direction is considered as a noise factor in the experiments. Finally, verification tests are carried out to investigate the improvement of the optimization. The results showed an improvement of 49.02 and 26.28 in the surface roughness and cutting force performance, respectively